Senior Azure Data Engineer

Location: Bulgaria, Poland, or Romania

Company

Global AI-first digital transformation and engineering partner delivering scalable products, platforms, data-driven solutions, and AI solutions across 16 countries.

What you will do

• Design, build, test, deploy, and maintain scalable data pipelines for reporting and analytics.
• Create production-ready pipelines and refactor existing pipelines to improve reliability, performance, maintainability, and observability.
• Collaborate with Data professionals, Data Architects, Product Managers, and Engineering Managers to translate reporting needs into technical solutions.
• Onboard Core Products data workloads onto the Data Platform while following architecture, governance, security, and engineering standards.
• Own SRE practices, monitor pipeline operations, diagnose incidents, identify root causes, and implement corrective actions.
• Document data flows, dependencies, transformation logic, operating procedures, and operational ownership while sharing engineering practices with the data team.

Requirements

• At least 8 years of professional Data Engineering experience, including ownership of production-grade data pipelines.
• Strong hands-on experience with Microsoft Azure and Databricks.
• Advanced SQL and Python skills.
• Experience with data-platform and lakehouse principles, including medallion architecture and dimensional modelling for reporting.
• Experience with software engineering and DataOps practices, including version control, automated testing, CI/CD, deployment, monitoring, and incident management.
• Strong stakeholder communication skills, autonomy, sound technical decision-making, and clear documentation.

Nice to have

• Experience with data governance, lineage, and access-control practices in Databricks, including Unity Catalog.
• Experience with payment or transaction data.
• Experience working in distributed international teams.

Culture & Benefits

• Engineering-focused environment with a people-first culture.
• Continuous growth and knowledge sharing across international data and engineering teams.
• Opportunity to contribute to the long-term autonomy of the Core Products data team.

Hiring process

• CV review.
• HR call, interview, and client interview.
• Final decision.